A rank order filter identifies the value of a particular rank in a set of data. A median filter, for example, is one type of rank order filter identifies the value that is in the midpoint of a dataset; that is, the value that equally divides the remaining values in the set such that half are larger and half are smaller than the median value. Other rank order filters may be used to identify values at different ranks within the dataset (e.g., bottom 25%, top 25%, etc.), as desired.
Many different types of median and other rank order filters have been widely used over many years in a multitude of settings. In signal processing applications, for example, it is often desirable to be able to perform some kind of noise reduction on an image or signal. The median filter is one type of nonlinear digital filtering technique that is often used to remove noise. Since the median function is not concerned with the particular values of outlying data, the median function can be very effective at ignoring the effects of relatively large magnitude noise within the dataset. For this reason, median filtering is very widely used in digital image processing because, under certain conditions, the median function preserves image edges while removing noise from the image. Median filters, as well as other types of rank order filters, are widely used in other applications as well.
Most current rank order filters, however, can demand relatively significant computing resources to provide accurate results within the time frames needed for certain applications. In particular, it can be computationally challenging to implement a rank order for a relatively large dataset, particularly using field programmable gate arrays or similar hardware logic devices. It is therefore desirable to provide a rank order filter that reliably yet efficiently identifies the value of a particular rank in a data set, such as the median value. These and other desirable features and characteristics will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and this background section.